Journals
Cyber risk assessment model for information assets: a tailored approach for the financial and banking sector
The authors present a novel model risk assessment model designed specifically for cyber risks and information assets,
Research on the multifractal volatility of Chinese banks based on the synthetic minority oversampling technique, edited nearest neighbors and long short-term memory
Artificial intelligence in crisis management: a bibliometric analysis
A qualitative study of operational resilience in financial institutions
The fundamental role of the repo market and central clearing
The authors evaluate different economic functions of repo contracts and offer a summary of the structure of government bond repo markets in core advanced economies.
Can tax evasion be reduced by fostering cashless payments? A systematic literature review
This paper offers a review of literature on how different payment methods impact tax evasion, finding cash to facilitate tax evasion and digital methods of payment to make evasion more difficult.
On par: a money view of stablecoins
The authors apply a money view analysis to stablecoins, revealing the character if existing on-chain liquidity mechanisms that support the premise of par settlement and finding liquidity rather than solvency to be the factor confronted by par settlement.
A model combining Optuna and the light gradient-boosting machine algorithm for credit default forecasting
The authors put forward a default prediction model designed to make the analysis of complex, highly dimensional and imbalanced real-world bank data easier.
Litigation risk assessment: a novel quantitative recency–frequency–monetary model
The authors assess litigation risk and credit risk of companies and investigate interrelationships between these risks, finding a correlation between them.
Unveiling multiscale dynamics: exploring financial risk spillover and influencing factors among Chinese financial institutions
The authors investigate financial risk spillover in Chinese financial institutions, identifying the important role played by such institutions in the transmission of network risk as well as the conditions which increase and decrease risk spillover.
Cumulative accuracy profile curves for correlating collateralized debt obligations to systematic factors
This paper proposes a means to calibrate the correlation for paper issued by a collateralized debt obligation is included in a general credit portfolio of corporate bonds.
Converting a covariance matrix from local currencies to a common currency
The authors put forward a simple means to translate a covariance matrix estimated in local currencies into a covariance matrix expressed in a common currency.
Analyzing credit risk model problems through natural language processing-based clustering and machine learning: insights from validation reports
The authors use clustering and machine learning techniques to analyze validation reports, providing insights to the development, implementation and maintenance of credit risk models.
Machine learning prediction of loss given default in government-sponsored enterprise residential mortgages
The authors apply machine learning techniques to Loss Given Default estimation, identifying key variables in LGD prediction and evaluating the performance of various models.
Forecasting India’s foreign trade dynamics: evaluation of alternative forecasting models in the post-pandemic period
The authors aim to determine how India's foreign trade will change following Covid-19 and the Russia-Ukraine conflict, comparing several forecasting models and identifying that which performs best.
Forecasting the Volatility Index with a realized measure, volatility components and dynamic jumps
The authors put forward the REGARCH-2C-Jump model to forecast VIX, with results suggesting that this model can outperform other models in VIX forecasting.
Pricing high-dimensional Bermudan options using deep learning and higher-order weak approximation
The authors propose a deep-learning-based algorithm for high-dimensional Bermudan option pricing with the novel feature of discretizing the interval between early-exercise dates using a higher-order weak approximation of stochastic differential equations.
Clustering market regimes using the Wasserstein distance
The authors apply Wasserstein distance and barycenter to the k-means clustering algorithm, validating their proposed method both qualitatively and quantitatively.
An iterative copula method for probability density estimation
This paper puts forward a technique with which to reconstruct a probability density function from an n-dimensional probability distribution sample and provide a theoretical justification for the proposed method.
The impact of deterioration in rating-model discriminatory power on expected losses
The authors propose a means to estimate the effects on a portfolio’s expected credit loss created by underwriting model risks.
Consumer credit card payment dynamics over the economic cycle
This papers uses data from 1.8 million credit card accounts to investigate how consumers revolve credit card debt and the impact of this on default risk.
Unaligned exchange traded funds: risk-adjusted performance and market-timing skills
The authors compare the performance of unaligned exchange-traded funds with US and global equities, finding a significant positive correlation in monthly returns.
Kernel-based estimation of spectral risk measures
The authors put forward a kernel-based estimator for spectral risk measures and compare its performance with existing SRM estimators.
Analyzing market sentiment based on the option-implied distribution of stock returns
The authors propose a means to assess market sentiment using the option-implied distribution of stock returns generated from option data, allowing for efficient optimization of complex portfolios.